Super-connected and hyper-connected jump graphs

Let G be a connected graph. The graph G is said to be super-connected if for every minimum vertex cut S of G, G?S has isolated vertices. Moreover, it is said to be hyper-connected if for every minimum vertex cut S, G?S has exactly two components, one of which is an isolated vertex. In this note, we give a necessary and sufficient condition for a graph G whose jump graph J(G) (the complement of line graph of G) is, respectively, super-connected and hyper-connected.     

Linear-time algorithm for the matched-domination problem in cographs

Let G=(V, E) be a graph without isolated vertices. A matching in G is a set of independent edges in G. A perfect matching M in G is a matching such that every vertex of G is incident to an edge of M. A set S? V is a paired-dominating set of G if every vertex not in S is adjacent to a vertex in S and if the subgraph induced by S contains a perfect matching. The paired-domination problem is to find a paired-dominating set of G with minimum cardinality. This paper introduces a generalization of the paired-domination problem, namely, the matched-domination problem, in which some constrained vertices are in paired-dominating sets as far as they can. Further, possible applications are also presented. We then present a linear-time constructive algorithm to solve the matched-domination problem in cographs.? ^?A preliminary version of this paper has appeared in: Proceedings of the 4th IASTED International Conference on Computational Intelligence (CI’2009), Honolulu, Hawaii, USA, 2009, pp. 120–126.      

图的有损摘要问题的两阶段算法

问题如下:给定图G=(V, E)和正整数k,要求将图G中所有节点合并成为k个超节点,满足由这些超节点组成的摘要图能够在一定误差范围内表示原图G.这是一个基于图划分的组合优化问题,一个主要求解思路是逐次地随机抽取节点对集并用启发式方法从中选取节点对进行合并.本文提出一个有效的两阶段求解算法TS＿LGS.算法根据图G的平均点度特征设置阶段阈值:当前超节点数大于阶段阈值为第1阶段,期间算法在采样节点对中基于当前最佳合并分数批量选择节点对合并,旨在有效减少迭代次数;否则为第2阶段,期间算法在加权采样的基础上优先挑选相邻的节点对,旨在找到重构误差增量较小的节点对合并,直至超节点的个数为k.在典型的真实网络实例图上与现有最好算法SAA进行了实验对比,结果表明,算法TS＿LGS以较低时间复杂度提取到的图摘要具有更低的重构误差和查询误差.     

Additive tree 2-spanners of permutation graphs

Let G be a connected graph. A spanning tree T of G is a tree t-spanner if the distance between any two vertices in T is at most t times their distance in G. If their distances in T and G differ by at most t, then T is an additive tree t-spanner of G. In this paper, we show that any permutation graph has an additive tree 2-spanner, and it can be found in O(n) time sequentially or in O(log n) time with O(n/log n) processors on the EREW PRAM computational model by using a previously published algorithm for finding a tree 3-spanner of a permutation graph.     

On fully orientability of 2-degenerate graphs

Suppose that D is an acyclic orientation of the graph G. An arc of D is dependent if its reversal creates a directed cycle. Let d(D) denote the number of dependent arcs in D. Define dmin(G) (dmax(G)) to be the minimum (maximum) number of d(D) over all acyclic orientations D of G. We call G fully orientable if G has an acyclic orientation with exactly k dependent arcs for every k satisfying dmin(G)?k?dmax(G). We prove that every 2-degenerate graph is fully orientable and give interpretations to their dmin.     

Vertex arboricity of planar graphs without chordal 6-cycles

The vertex arboricity va(G) of a graph G is the minimum number of colours the vertices can be coloured so that each colour class induces a forest. It was known that va(G)≤3 for every planar graph G, and the problem of computing vertex arboricity of graphs is NP-hard. In this paper, we prove that va(G)≤2 if G is a planar graph without chordal 6-cycles. This extends a result by Raspaud and Wang [On the vertex-arboricity of planar graphs, Eur. J. Combin. 29 (2008), pp. 1064–1075].     

Branch-bonds,two-factors in iterated line graphs and circuits in weighted graphs

A nontrivial path is called a branch if it has only internal vertices of degree two and end vertices of degree not two. A set S of branches of a graph G is called a branch cut if the deletion of all edges and internal vertices of branches of S results in more components than G. A minimal branch cut is called a branch-bond. In this paper, we found some relationships amongst branch-bonds, weighted graphs and two-factors in iterated line graphs. We also obtained some bounded number of components in two-factor of iterated line graphs by using the concept of branch-bonds.     

Multicolorings of Series-Parallel Graphs

Let G be a graph, and let each vertex v of G have a positive integer weight ω(v). A multicoloring of G is to assign each vertex v a set of ω(v) colors so that any pair of adjacent vertices receive disjoint sets of colors. This paper presents an algorithm to find a multicoloring of a given series-parallel graph G with the minimum number of colors in time O(n W), where n is the number of vertices and W is the maximum weight of vertices in G.     

A New Approximation Algorithm for Finding Heavy Planar Subgraphs

Abstract. We provide the first nontrivial approximation algorithm for MAXIMUM WEIGHT PLANAR SUBGRAPH, the NP-hard problem of finding a heaviest planar subgraph in an edge-weighted graph G . This problem has applications in circuit layout, facility layout, and graph drawing. No previous algorithm for MAXIMUM WEIGHT PLANAR SUBGRAPH had a performance ratio exceeding 1/3 , which is obtained by any algorithm that produces a maximum weight spanning tree in G . Based on the Berman—Ramaiyer Steiner tree algorithm, the new algorithm has performance ratio at least 1/3+1/72 and at most 5/12 . We also show that if G is complete and its edge weights satisfy the triangle inequality, then the performance ratio is at least 3/8 . Furthermore, we derive the first nontrivial performance ratio (7/12 instead of 1/2 ) for the NP-hard SC MAXIMUM WEIGHT OUTERPLANAR SUBGRAPH problem.     

A sufficient condition for a graph to be an (a,b, k)-critical graph

Let G be a graph, and let a, b, k be integers with 0≤a≤b, k≥0. An [a, b]-factor of graph G is defined as a spanning subgraph F of G such that a≤d _F (x)≤b for each x∈V(G). Then a graph G is called an (a, b, k)-critical graph if after deleting any k vertices of G the remaining graph of G has an [a, b]-factor. In this article, a sufficient condition is given, which is a neighborhood condition for a graph G to be an (a, b, k)-critical graph.     

On maximal 3-restricted edge connectivity of regular graphs

Let G be a k-regular graph of order at least nine. It is proved in this work that graph G is maximally 3-restricted edge-connected if it is triangle-free and k>|G|/4+1, the lower bound on k is sharp to some extent. With this observation, we present an expression of the number of edge cuts in the previous graph, which may be employed to analyse the reliability of telecommunication networks.     

The algorithmic complexity of mixed domination in graphs

Let G=(V,E) be a simple graph with vertex set V and edge set E. A subset W⊆V∪E is a mixed dominating set if every element x∈(V∪E)?W is either adjacent or incident to an element of W. The mixed domination problem is to find a minimum mixed dominating set of G. In this paper we first prove that a connected graph is a tree if and only if its total graph is strongly chordal, and thus we obtain a polynomial-time algorithm for this problem in trees. Further we design another linear-time labeling algorithm for this problem in trees. At the end of the paper, we show that the mixed domination problem is NP-complete even when restricted to split graphs, a subclass of chordal graphs.     

A Cubic Kernel for Feedback Vertex Set and Loop Cutset

The Feedback Vertex Set problem on unweighted, undirected graphs is considered. Improving upon a result by Burrage et al. (Proceedings 2nd International Workshop on Parameterized and Exact Computation, pp. 192–202, 2006), we show that this problem has a kernel with O(k ³) vertices, i.e., there is a polynomial time algorithm, that given a graph G and an integer k, finds a graph G′ with O(k ³) vertices and integer k′≤k, such that G has a feedback vertex set of size at most k, if and only if G′ has a feedback vertex set of size at most k′. Moreover, the algorithm can be made constructive: if the reduced instance G′ has a feedback vertex set of size k′, then we can easily transform a minimum size feedback vertex set of G′ into a minimum size feedback vertex set of G. This kernelization algorithm can be used as the first step of an FPT algorithm for Feedback Vertex Set, but also as a preprocessing heuristic for Feedback Vertex Set.     

Power Domination in Circular-Arc Graphs

A set S?V is a power dominating set (PDS) of a graph G=(V,E) if every vertex and every edge in G can be observed based on the observation rules of power system monitoring. The power domination problem involves minimizing the cardinality of a PDS of a graph. We consider this combinatorial optimization problem and present a linear time algorithm for finding the minimum PDS of an interval graph if the interval ordering of the graph is provided. In addition, we show that the algorithm, which runs in Θ(nlogn) time, where n is the number of intervals, is asymptotically optimal if the interval ordering is not given. We also show that the results hold for the class of circular-arc graphs.     

Parameterized complexity of connected even/odd subgraph problems

In 2011, Cai an Yang initiated the systematic parameterized complexity study of the following set of problems around Eulerian graphs: for a given graph G and integer k, the task is to decide if G contains a (connected) subgraph with k vertices (edges) with all vertices of even (odd) degrees. They succeed to establish the parameterized complexity of all cases except two, when we ask about:

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a connected k-edge subgraph with all vertices of odd degrees, the problem known as k-Edge Connected Odd Subgraph; and     

Indexing through laplacian spectra

With ever growing databases containing multimedia data, indexing has become a necessity to avoid a linear search. We propose a novel technique for indexing multimedia databases in which entries can be represented as graph structures. In our method, the topological structure of a graph as well as that of its subgraphs are represented as vectors whose components correspond to the sorted laplacian eigenvalues of the graph or subgraphs. Given the laplacian spectrum of graph G, we draw from recently developed techniques in the field of spectral integral variation to generate the laplacian spectrum of graph G+e without computing its eigendecomposition, where G+e is a graph obtained by adding edge e to graph G. This process improves the performance of the system for generating the subgraph signatures for 1.8% and 6.5% in datasets of size 420 and 1400, respectively. By doing a nearest neighbor search around the query spectra, similar but not necessarily isomorphic graphs are retrieved. Given a query graph, a voting schema ranks database graphs into an indexing hypothesis to which a final matching process can be applied. The novelties of the proposed method come from the powerful representation of the graph topology and successfully adopting the concept of spectral integral variation in an indexing algorithm. To examine the fitness of the new indexing framework, we have performed a number of experiments using an extensive set of recognition trials in the domain of 2D and 3D object recognition. The experiments, including a comparison with a competing indexing method using two different graph-based object representations, demonstrate both the robustness and efficacy of the overall approach.     

Maximum Induced Matchings for Chordal Graphs in Linear Time

The Maximum Induced Matching (MIM) Problem asks for a largest set of pairwise vertex-disjoint edges in a graph which are pairwise of distance at least two. It is well-known that the MIM problem is NP-complete even on particular bipartite graphs and on line graphs. On the other hand, it is solvable in polynomial time for various classes of graphs (such as chordal, weakly chordal, interval, circular-arc graphs and others) since the MIM problem on graph G corresponds to the Maximum Independent Set problem on the square G ^*=L(G)² of the line graph L(G) of G, and in some cases, G ^* is in the same graph class; for example, for chordal graphs G, G ^* is chordal. The construction of G ^*, however, requires time, where m is the number of edges in G. Is has been an open problem whether there is a linear-time algorithm for the MIM problem on chordal graphs. We give such an algorithm which is based on perfect elimination order and LexBFS.